When test results begin to shift from one operator to the next, the typical reaction is more training. Experienced technicians are retiring faster than they can be replaced, and new hires are expected to be up to speed in weeks, not years. However, operator variation in testing of paints and coatings is not primarily a training gap; it is usually a problem within the system itself. User variation is often a contributing factor, but it is also typically accompanied by confusing procedures, instrumentation/ tooling inconsistency and subjective results. This article identifies process variation points by examining the defined system. It explores solutions to improve physical test systems and provides application guidance that can help ensure every result can be a reliable benchmark and indicator in your process.

I. The Question Every Lab Should Ask

Would your test results be consistent if a new operator ran them tomorrow?

This question is essential but uncomfortable for many paint and coating labs.

Laboratories are facing constant pressure with experienced technicians retiring, large turnovers, and high expectations of new hires to master methods quickly. However, two trained operators can run the same viscosity or adhesion test on the same coating and arrive at different results. Both followed the written procedure. Both completed the required training. Yet the numbers do not align.

Once discrepancies are found, the response is typically more training or shadowing, rarely addressing the root cause. Often times, the real issue is not how the operator runs the test, but how the test system is designed. Systems that depend on experience or intuition alone turn standardized methods into “handiwork”, limiting reliability as the workforce changes.

II. Why Operator Variation Is a System Problem — Not the Operator

Training in paint and coatings laboratories, as well as in manufacturing quality assurance, evolved from skilled craftsmanship where techniques and expertise were learned through observation and repetition, passed down by experienced technicians who had accumulated decades of experience. Today’s workforce is very different. Many tenured experts are retiring while organizations expect operators to cross-function and new hires to contribute quickly. These conditions cause variability with test methods that rely on subtle techniques or unwritten judgment, meaning quality decisions may depend on who ran the test rather than on a dependable measurement system.

When you break it down further, variation in test methods is usually found when there are sensitive steps, subjectivity in visual assessments, and instrument interfaces that provide little guidance. Such weaknesses magnify slight differences into problematic result shifts. The main goal is to design systems that minimize avoidable operator influence and protect result integrity through clear procedures, objective measurement criteria, and instruments that guide users toward consistent execution regardless of experience level.

III. Design Features That Reduce Operator Dependency

Physical test systems should also be designed to reduce operator dependency, building consistency in the equipment and the process. Guided setup features, clear feedback, minimal manual adjustments, and standardized accessories help cut variability by making correct operation intuitive and repeatable. Complementing this with visual application guidance, such as step-by-step manuals, how-to videos, and checklists, ensures operators follow the same procedures. This ultimately reduces technique differences, minimizes subjective input, and enables more consistent, reproducible results across each user.

IV. How Test Systems Help Safeguard Results

Rather than utilizing standalone devices, working with a testing partner that emphasizes integrated test systems is preferred due to the tailored assistance and experience that can be provided. A comprehensive test system includes the primary measurement instrument, calibration standards, application-specific accessories, standardized procedures, and supporting tools that work together to ensure consistency, meet specifications, and reduce operator variability. For example, a viscosity testing system includes the cup, certified reference fluids, cleaning tools, temperature-monitoring equipment, and standardized procedures, all delivering repeatable, reliable measurements across different operators and testing environments.

Equally important is a testing partner’s investment in education and operator guidance through knowledge libraries, application notes, and how-to videos that translate industry standards into clear, repeatable steps. These resources provide the missing need for most testing systems across paints and coatings manufacturing.

V. Practical Checklist: Is Your Test a System Problem?

It’s important to identify where your testing system lacks before exploring solutions to enhance overall reliability. Use the checklist below as a quick diagnostic to evaluate your current methods: 

Tests that often produce different outcomes depending on who runs them should be treated as candidates for redesign, not just retraining. Focus on the process by improving procedures, reducing subjectivity, or upgrading equipment that can meet repeatability expectations. Each helps to mitigate inconsistent results across users in the entire system. Overall, this approach is far more effective than trying to train around a fundamentally inconsistent process.

VI. Next Steps for Quality Leaders

To effectively reduce measurement risk, examine your current testing processes and identify methods most sensitive to operator technique, and the areas where slight differences lead to inconsistent or misleading results. Talk directly with operators to identify unclear procedures, methods that are hard to keep consistent, and steps that require too much individual judgment. This perspective is key to understanding how processes actually work day-to-day and where to focus training and competency efforts on higher-risk tasks.

Often, this review also highlights tools or setups that aren’t performing as they should. In those cases, improvements to instrumentation, fixturing, or written procedures can reduce variability and deliver more consistent results across different users, strengthening the overall measurement system beyond training alone.

When framed the right way, these changes go beyond just upgrading equipment. They’re a practical response to a changing workforce, where experience levels vary and time for training is often limited. Strengthening the testing process improves consistency, protects data integrity, and supports long-term improvement.

Which brings it back to a simple but important question: are your current paint and coatings tests set up to deliver consistent results, no matter who is running them?

Conclusion

Consistency in testing is not achieved by pushing people to perform better within a flawed system, but rather by building a process that is reliable from the start. When methods are clear, repeatable, and less dependent on individual opinion/technique, the entire operation becomes more stable and easier to manage. That shift not only improves data quality but also reduces the daily friction operators face when seeking dependable results. As teams, tools, and demands continue to evolve, the organizations that stay ahead will be those that treat testing as a system for refinement, not just a task to execute. Taking the time to strengthen methods, reduce subjectivity, and align processes with real-world conditions pays off in more reliable results and fewer surprises. In the end, the goal is straightforward: a testing process that can be trusted for data driven improvement and innovation. 

For more information, call (954) 946-9454 or (800) 762-2478, email [email protected] or visit www.gardco.com.